
<h1><span class="yiyi-st" id="yiyi-12">numpy.fft.irfft2</span></h1>
        <blockquote>
        <p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.fft.irfft2.html">https://docs.scipy.org/doc/numpy/reference/generated/numpy.fft.irfft2.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
<dl class="function">
<dt id="numpy.fft.irfft2"><span class="yiyi-st" id="yiyi-13"> <code class="descclassname">numpy.fft.</code><code class="descname">irfft2</code><span class="sig-paren">(</span><em>a</em>, <em>s=None</em>, <em>axes=(-2</em>, <em>-1)</em>, <em>norm=None</em><span class="sig-paren">)</span><a class="reference external" href="http://github.com/numpy/numpy/blob/v1.11.3/numpy/fft/fftpack.py#L1214-L1247"><span class="viewcode-link">[source]</span></a></span></dt>
<dd><p><span class="yiyi-st" id="yiyi-14">计算实数组的二维逆FFT。</span></p>
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<tr class="field-odd field"><th class="field-name"><span class="yiyi-st" id="yiyi-15">参数：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-16"><strong>a</strong>：array_like</span></p>
<blockquote>
<div><p><span class="yiyi-st" id="yiyi-17">输入数组</span></p>
</div></blockquote>
<p><span class="yiyi-st" id="yiyi-18"><strong>s</strong>：ints序列，可选</span></p>
<blockquote>
<div><p><span class="yiyi-st" id="yiyi-19">逆FFT的形状。</span></p>
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<p><span class="yiyi-st" id="yiyi-20"><strong>axes</strong>：ints序列，可选</span></p>
<blockquote>
<div><p><span class="yiyi-st" id="yiyi-21">计算反向fft的轴。</span><span class="yiyi-st" id="yiyi-22">默认值是最后两个轴。</span></p>
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<p><span class="yiyi-st" id="yiyi-23"><strong>norm</strong>：{None，“ortho”}，可选</span></p>
<blockquote>
<div><div class="versionadded">
<p><span class="yiyi-st" id="yiyi-24"><span class="versionmodified">版本1.10.0中的新功能。</span></span></p>
</div>
<p><span class="yiyi-st" id="yiyi-25">规范化模式（参见<a class="reference internal" href="../routines.fft.html#module-numpy.fft" title="numpy.fft"><code class="xref py py-obj docutils literal"><span class="pre">numpy.fft</span></code></a>）。</span><span class="yiyi-st" id="yiyi-26">默认值为None。</span></p>
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<tr class="field-even field"><th class="field-name"><span class="yiyi-st" id="yiyi-27">返回：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-28"><strong>out</strong>：ndarray</span></p>
<blockquote class="last">
<div><p><span class="yiyi-st" id="yiyi-29">反向实数2-D FFT的结果。</span></p>
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<div class="admonition seealso">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-30">也可以看看</span></p>
<dl class="last docutils">
<dt><span class="yiyi-st" id="yiyi-31"><a class="reference internal" href="numpy.fft.irfftn.html#numpy.fft.irfftn" title="numpy.fft.irfftn"><code class="xref py py-obj docutils literal"><span class="pre">irfftn</span></code></a></span></dt>
<dd><span class="yiyi-st" id="yiyi-32">计算实际输入的N维FFT的逆。</span></dd>
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<p class="rubric"><span class="yiyi-st" id="yiyi-33">笔记</span></p>
<p><span class="yiyi-st" id="yiyi-34">这真的是<a class="reference internal" href="numpy.fft.irfftn.html#numpy.fft.irfftn" title="numpy.fft.irfftn"><code class="xref py py-obj docutils literal"><span class="pre">irfftn</span></code></a>具有不同的默认值。</span><span class="yiyi-st" id="yiyi-35">有关详细信息，请参阅<a class="reference internal" href="numpy.fft.irfftn.html#numpy.fft.irfftn" title="numpy.fft.irfftn"><code class="xref py py-obj docutils literal"><span class="pre">irfftn</span></code></a>。</span></p>
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